One in three women will be affected by osteoporosis in their lifetimes, and detecting who is most at risk is part of UC Berkeley Mechanical Engineering Professor Tony Keaveny’s research. Keaveny and other CITRIS colleagues combine biomechanics with medical imaging to provide better diagnosis of osteoporosis risk of fracture. They are working in a new paradigm in healthcare—the seamless use of advanced physiological modeling of 3D medical images, or “virtual stress testing.” The new application will inform about a patient’s condition in a way that is scientifically accurate, intuitive, and compelling.
The application for fracture risk assessment in osteoporosis is based on the basic biomechanical characteristics of bone at multiple physical scales. Patient-specific structural models are created for a bone using clinical CT scans to calculate the bone strength in a highly automated process. Studies have shown that these estimates of strength are superior to what can be provided with the current clinical standard, a DXA (dual energy X-ray absorptiometry) bone scan. With the addition of estimates of the in vivo forces that occur during strenuous activity, researchers can better estimate a biomechanical risk of fracture.
Through collaboration with the UC Berkeley Parallel Computing Lab (Parlab), Professor Keaveny now plans to extend this technology to address coronary heart disease (CHD), which affects 16 million Americans annually and is associated with over 400,000 deaths per year. Their vision is that future radiological diagnostic procedures will be interpreted using such quantitative physiological patient-specific models, thus transforming The field of radiology and improving healthcare by better identifying those at high risk for various diseases.